Playing games with AI
Artificial Intelligence (AI) is a serious subject. In a practical sense, it’s already transforming numerous sectors, from fashion to the automotive industry and everything in between. In a more theoretical sense, billions are pumped into asking big questions, like: does AI pose an existential threat to the species (Elon Musk and Oxford philosopher Nick Bostrom)? Are self-improving AIs about to usher in a new age of ‘super-intelligence’ (Google’s chief futurist, Ray Kurzweil)?
Given the enormous ramifications that both the practical and theoretical issues around AI have for our future, why do the people creating it seem so intent on forcing it to play board and card games?
Google’s DeepMind is possible the world’s pre-eminent AI researcher. Its program, AlphaGo, made history by defeating the world’s greatest living Go master, Lee Sedol. Go is a game of strategy, created in China and popular all round Asia, that is considered the world’s most challenging strategy game. Like Chess, it requires incredible levels of strategic intelligence, working memory, and predictive ability. But it’s complexity is far greater than Chess, and this means there is an element of creativity to the game – it is simply not possible to compute all the possible moves on a Go board, meaning the best players often have an intuitive, hard to analyse, style.
Alphabet’s share price has risen by 21% so far this year
It’s not the kind of thing a machine should be able to beat a human in. So when AlphaGo did, it signified a new horizon for AI: computers could now learn in real time, and form experience, like a human.
Poker, Chess, and Go are just some of the games in which AI is no outstripping human players. But the purpose of these AIs is not to raise the caliber of competitive strategy games to post-human levels: it’s to build up important cognitive tools to apply to real world problems that require strategic decision making abilities.
Noam Brown, a Carnegie Mellon phd student in computer science, explains that AI is becoming more flexible than people think:
“People have a misunderstanding of what computers and people are each good at. People think that bluffing is very human – it turns out that’s not true. A computer can learn from experience that if it has a weak hand and it bluffs, it can make more money.”
Dominion holds Alphabet, the parent company of Google, in its Global Trends Managed Fund.
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